class_docstr: This class allows you to specify skipping a ``Seq2SeqEncoder`` just
  by changing a configuration file. This is useful for ablations and
  measuring the impact of different elements of your model.
code: def __init__(self, input_dim):
      super(PassThroughEncoder, self).__init__()
      self._input_dim = input_dim
  
file_path: magnitude/pymagnitude/third_party/allennlp/modules/seq2seq_encoders/pass_through_encoder.py
imports: from __future__ import absolute_import
  import torch
  from allennlp.modules.seq2seq_encoders.seq2seq_encoder import Seq2SeqEncoder
label_desc: Use image node_id 1 to create a new PassThroughEncoder object from inherited base classes: Seq2SeqEncoder with example: obj = PassThroughEncoder(input_dim)